Abstracts

This study analyzed the association between the inversion of traditional gender roles and exclusive psychological and physical/sexual intimate partner violence, in a cross-sectional study of Brazilian pregnant women, identified through prenatal services in the municipalities of São Luís, Maranhão State (n = 992) and Ribeirão Preto, São Paulo State (n = 943). The pregnant women ranged from 12 to 45 years. Inversion of traditional gender roles was assessed by calculating differences in age, education and occupation between pregnant women and their co-residing intimate partners and identifying the largest contribution to family income. The conceptual model was tested with structural equation modeling and showed acceptable fit. The prevalence of any type of intimate partner violence was 29.8% in São Luís and 20.1% in Ribeirão Preto. In both municipalities, pregnant women were more likely to suffer exclusive psychological and physical/sexual violence when they had the highest income in the family (p < 0.005). In São Luís, physical/sexual violence was more common among women who were better educated than their partners (standardized coefficient, SC = -0.466; p = 0.007). In Ribeirão Preto, exclusive psychological violence was more frequent among women who had lower status occupations than their partners (SC = 0.236; p = 0.004). Inversion of traditional gender roles is associated with exclusive psychological and physical/sexual violence against pregnant women by their co-residing intimate partners. These findings suggest that women's empowerment at an individual level does not necessarily relieve them of intimate partner abuse in social contexts where traditional gender norms persist.

Introduction

Intimate partner violence is a global public health problem and a common form of violence against women, with multiple negative repercussions for the health and well-being of women and their families 11. Word Health Organization. Global and regional estimates of violence against women: prevalence and health effects of intimate partner violence and non-partner sexual violence. Geneva: Word Health Organization; 2013.,22. Inter-Agency Standing Committee. Guidelines for integrating gender-based violence interventions in humanitarian action: reducing risk, promoting resilience and aiding recovery. Geneva: Word Health Organization; 2015.. Intimate partner violence is frequently linked to lower socioeconomic contexts 33. World Health Organization. WHO multi-country study of women's health and domestic violence against women: summary report of initial results on prevalence, health outcomes and women's responses. Geneva: Word Health Organization; 2005.,44. Heise L, Kotsadam A. Cross-national and multilevel correlates of partner violence: an analysis of data from population-based surveys. Lancet Glob Health 2015; 3:e332-e40., and is also considered a manifestation of gender-based violence, exposing power inequalities in relationships and the domination of and discrimination against women by men 22. Inter-Agency Standing Committee. Guidelines for integrating gender-based violence interventions in humanitarian action: reducing risk, promoting resilience and aiding recovery. Geneva: Word Health Organization; 2015.,55. United Nations. Review and appraisal of the implementation of the Beijing declaration and platform for action and the outcomes of the twenty-third special session of the General Assembly. New York: United Nations; 2014..

Worldwide, about 38% of women with an intimate partner report having suffered physical and/or sexual violence committed by a current or former partner 11. Word Health Organization. Global and regional estimates of violence against women: prevalence and health effects of intimate partner violence and non-partner sexual violence. Geneva: Word Health Organization; 2013.. However, the rates range from 4% in high income countries to more than 40% in low income contexts 11. Word Health Organization. Global and regional estimates of violence against women: prevalence and health effects of intimate partner violence and non-partner sexual violence. Geneva: Word Health Organization; 2013.,33. World Health Organization. WHO multi-country study of women's health and domestic violence against women: summary report of initial results on prevalence, health outcomes and women's responses. Geneva: Word Health Organization; 2005.,44. Heise L, Kotsadam A. Cross-national and multilevel correlates of partner violence: an analysis of data from population-based surveys. Lancet Glob Health 2015; 3:e332-e40.,66. Breiding MJ, Basile KC, Smith SG, Black MC, Mahendra RR. Intimate partner violence surveillance: uniform definitions and recommended data elements. Atlanta: National Center for Injury Prevention and Control/Centers for Disease Control and Prevention; 2015.,77. Antai D, Antai J, Anthony DS. The relationship between socio-economic inequalities, intimate partner violence and economic abuse: a national study of women in the Philippines. Glob Public Health 2014; 9:808-26.. In Brazil, the WHO Multi-Country Study on women’s health and domestic violence against women found a 46.4% prevalence of some type of Intimate partner violence in São Paulo, the largest Brazilian metropolis, and a 54.2% prevalence in the Zona da Mata of Pernambuco, an urban-rural area. The prevalence of physical violence against pregnant women was 8% for São Paulo and 11.1% for Pernambuco 33. World Health Organization. WHO multi-country study of women's health and domestic violence against women: summary report of initial results on prevalence, health outcomes and women's responses. Geneva: Word Health Organization; 2005..

Inequalities between women and men in their socially attributed roles and the way masculinity and femininity are understood in the family or other social institutions are historically determined. Many of them represent obstacles for women to thrive and have served to perpetuate gender-based violence and to prevent access to formal wage employment and secondary education 11. Word Health Organization. Global and regional estimates of violence against women: prevalence and health effects of intimate partner violence and non-partner sexual violence. Geneva: Word Health Organization; 2013.,44. Heise L, Kotsadam A. Cross-national and multilevel correlates of partner violence: an analysis of data from population-based surveys. Lancet Glob Health 2015; 3:e332-e40.,55. United Nations. Review and appraisal of the implementation of the Beijing declaration and platform for action and the outcomes of the twenty-third special session of the General Assembly. New York: United Nations; 2014..

However, women's empowerment in a society with patriarchal and macho characteristics does not make them free from violence by an intimate partner. Older, more educated, better paid or women engaged in occupations of higher social status can be seen as a threat to male authority in the household-family environment, resulting in the use of violence by men to maintain their power 1111. Schraiber LB, d'Oliveira AFPL, Falcão NTC, Figueiredo WS. Violência dói e não é direito: a violência contra a mulher, a saúde e os direitos humanos. São Paulo: Universidade Estadual Paulista; 2005.,1212. Luke N, Schuler SR, Mai BTT, Thien PV. Minh TH. Exploring couple attributes and attitudes and marital violence in Vietnan. Violence Against Women 2007; 13:5-27.,1313. Bjelland HF. En voldsom maktbalanse? En studie av relativ makt og forekomst av partnervold. Sosiologisk Tidsskrift 2014; 22:51-74..

In a sample of pregnant women, this study hypothesizes that in a cultural context where males are valued more than females, women empowered through education and/or work may suffer increased intimate partner violence by challenging hierarchical gender norms. A second hypothesis tested in this study is that women older than their partners are at increased risk of intimate partner violence. Thus, the objective of this study was to investigate the impact of inverted traditional gender roles on intimate partner violence against pregnant women.

Method

This cross-sectional study is nested in the Brazilian Ribeirão Preto and São Luís Birth Cohort Studies (BRISA in the Portuguese acronym), which investigated the etiological factors of preterm birth in two Brazilian municipalities with contrasting socioeconomic contexts, i.e., São Luís (Maranhão/Brazil) and Ribeirão Preto (São Paulo/Brazil).

Participants, samples and data collection in the BRISA prenatal cohort

In the BRISA study, convenience samples were recruited due to the difficulty of obtaining a random sample from the population of pregnant women in São Luís and Ribeirão Preto.

The pregnant women recruited to the study were users of public or private prenatal care clinics and ultrasound services. Those with less than 20 weeks of gestational age were invited to participate when they satisfied the following criteria: having performed their first ultrasound test before 20 weeks of gestational age, having a singleton pregnancy and intending to give birth at one of the maternity hospitals of São Luís and Ribeirão Preto. The women who agreed to participate in the study were registered for an interview that took place from 20 to 25 weeks of gestational age. All pregnant women gave written informed consent before application of the questionnaires and completion of the tests, and responsible guardians provided consent for adolescents aged up to 17 years.

From February 2010 to June 2011, 1,447 pregnant women were interviewed in São Luís. In Ribeirão Preto, 1,400 women were interviewed from February 2010 to February 2011. A total of 410 women from São Luís and 435 from Ribeirão Preto were excluded from this analysis because they did not respond to the questions about violence, did not identify who perpetrated the violence against them or were victims of violence perpetrated by non-intimate partners (by family members, friends, acquaintances or unknown agents). Furthermore, 45 women in São Luís and 22 in Ribeirão Preto were not interviewed at the birth of their children. Thus, the final São Luís and Ribeirão Preto samples consisted of 992 and 943 pregnant women, respectively. The smallest sample size obtained (n = 943) can be used to identify differences between proportions of 8% for prevalence around 20% with 90% power.

Interviews were held in a private room to ensure confidentiality and were all performed by female interviewers. Questions about violence and social support were asked as part of a self-completed questionnaire and information about demographic and socioeconomic characteristics was obtained in interviews.

Training of interviewers consisted of detailed description of the research objectives and methods, data collection logistics, reading and discussion of all questionnaires and instructions manuals. Interviewers performed three interviews under strict supervision when errors were detected and corrected. A pilot study was performed to ensure that all phases of data collection were being performed correctly. Since questions about violence were self-applied and confidential, interviewers were not aware of the respondent’s answers. Women were instructed to look for services and support networks in cases of violence.

Variables and conceptual model

In the conceptual model (Figure 1), the variable woman’s self-reported skin color occupied the most distal position, followed by socioeconomic status, woman’s religion, variables that measured the inversion of traditional gender roles of the women and their co-residing intimate partners and social support, with exclusive psychological and physical/sexual violence by intimate partner as the outcomes. The variables woman’s self-reported skin color, socioeconomic status and woman’s religion were treated as confounders.

Socioeconomic status, social support and physical/sexual violence were analyzed as latent variables (or constructs). Socioeconomic status was investigated as a first-order factor and social support as a second-order factor. Exclusive psychological violence was investigated as an ordinal categorical variable and physical/sexual violence as a first-order latent variable.

The variables woman’s self-reported skin color (skin) and woman’s religion (relig) were collected after delivery before hospital discharge (from May 2010 to November 2011). Woman’s self-reported skin color was used as an exogenous dichotomous variable, categorized into white vs non-white. Woman’s religion was categorized into Catholic and Evangelical, the two predominant religions in Brazil.

Socioeconomic status was defined as the relative socioeconomic position that the individual or group occupies in a society 1717. American Psychological Association. Report of the APA task force on socioeconomic status. Washington DC: American Psychological Association; 2007.. The latent variable socioeconomic status was constructed based on the following indicator variables: (a) years of study of the pregnant woman (edu), categorized as up to 4 years, 5 to 8 years, 9 to 11 years, and 12 years or more; (b) occupation of the person with the highest income in the family (occu), categorized as unskilled manual, semi-specialized manual, office duties, high-level professional, and administrator/manager/director/owner; (c) economic class (class), categorized as D/E, C and A/B, consisting of ownership of assets (color television, radio, bathroom, automobile, full-time maid, washing machine, videocassette and/or DVD player, freezer, and refrigerator) and educational level of the person with the highest income in the family, with categories A and B having greater purchasing power; and (d) monthly family income in minimum wages (inc), categorized as less than one national minimum wage (approximately USD 290.00) for 2010, 1 to less than 3, 3 to less than 5, and 5 or more. The instrument used to measure economic class was that proposed by the Brazilian Association of Research Companies for 2010 1818. Associação Brasileira de Empresas de Pesquisas. Critério de classificação econômica Brasil 2010. http://www.abep.org/criterio-brasil (accessed on 13/Jun/2019).http://www.abep.org/criterio-brasil... .

Inequalities in relationships between women and their co-residing intimate partners reflecting inversion of traditional gender roles were measured as differences between intimate partners in terms of age, education and occupation, and by the highest financial contribution to the family as well. Inequalities in relationships have been defined as expression of gender conflicts when they represent inversions of socially expected roles within traditional gender culture 44. Heise L, Kotsadam A. Cross-national and multilevel correlates of partner violence: an analysis of data from population-based surveys. Lancet Glob Health 2015; 3:e332-e40.,55. United Nations. Review and appraisal of the implementation of the Beijing declaration and platform for action and the outcomes of the twenty-third special session of the General Assembly. New York: United Nations; 2014.,1919. Word Health Organization. Preventing intimate partner and sexual violence against women: taking action and generating evidence. Geneva: Word Health Organization; 2010..

Age differences (difage) between co-residing intimate partners were coded as follows: “1” if the woman’s age minus partner’s age > 5 years; “2” if the woman’s age minus partner’s age = 1 to 5 years; “3” woman’s age minus partner’s age = 0; “4” if partner’s age minus woman’s age = 1 to 5 years; and “5” if partner’s age minus woman’s age > 5 years.

Differences in years of education (difedu) and occupation (difoccu) between co-residing intimate partners were coded as follows: (a) “1” if the situation of the pregnant woman was superior to that of her intimate partner; “2” if the situation of the pregnant woman was equal to that of her intimate partner; and “3” if the situation of the pregnant woman was inferior to that of her intimate partner. The following occupations were considered in increasing hierarchical order: unskilled manual, semi-specialized manual, office duties, high-level professional, and administrator/manager/director/owner.

The person making the greatest contribution to family income (fam) was coded as: 1 = the pregnant woman; 2 = any subjects other than the pregnant woman or her partner; and 3 = the intimate partner.

Social support concerns resources offered by a social network to individuals in situations of need 2020. Cohen S, Underwood LG, Gottlieb BH. Social support measurement and intervention: a guide for health and social scientists. New York: Oxford University Press; 2000.,2121. Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med 1991; 32:705-14. and was measured as functional social support (supp) as proposed by the Medical Outcomes Study (MOS). Four dimensions of functional social support (supp) were evaluated: tangible support, emotional/informational support, affectionate support, and positive social interaction support. The five response options were never, rarely, at times, almost always, and always 2121. Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med 1991; 32:705-14..

intimate partner violence was considered to have occurred when the interviewed woman responded affirmatively to at least one of the 13 questions of the World Health Organization Violence against Women (WHO-VAW) instrument 2222. World Health Organization. Estudo multi-países sobre saúde da mulher e violência doméstica, versão 9.1. São Paulo: Faculdade de Medicina, Universidade de São Paulo; 2000. and indicated as the perpetrator a current/former intimate partner. Based on this definition, the overall intimate partner violence prevalence and the prevalence of the psychological, physical and sexual types were calculated (Table 1).

For psychological violence, the pregnant women were asked about insults, humiliations, intimidation and threats during the current pregnancy. Regarding physical violence during pregnancy, the women interviewed reported slaps, shoves, shakes, punches, kicks, strangling, deliberate burns and the use of weapons against them. Regarding sexual violence, they were asked about forced sex relations and sexual practices considered to be humiliating. The response options for each of these questions were none, once, a few times, and many times 2222. World Health Organization. Estudo multi-países sobre saúde da mulher e violência doméstica, versão 9.1. São Paulo: Faculdade de Medicina, Universidade de São Paulo; 2000.. In the present study, women submitted to physical and sexual violence were excluded from the investigation of exclusive psychological violence by the intimate partner. The questions were formulated exactly as in the WHO-VAW instrument 2222. World Health Organization. Estudo multi-países sobre saúde da mulher e violência doméstica, versão 9.1. São Paulo: Faculdade de Medicina, Universidade de São Paulo; 2000., without mentioning the word violence.

Descriptive analysis and structural equation modeling

Frequencies and percentages were calculated using Stata software, version 15.1 (https://www.stata.com). Structural equation modeling (SEM) was used to evaluate the conceptual model through the Mplus software, version 7.31 (https://www.statmodel.com/). SEM was chosen over multiple linear regression as it allowed us to consider measurement error by modeling violence as a latent variable and to estimate direct and indirect effects of the observed and latent variables on psychological and physical/sexual violence 2525. Kline RB. Principles and practice of structural equation modeling. New York: The Guilford Press; 2016..

Since all variables were encoded categorically, the mean-and-variance-adjusted weighted least squares estimator with theta parameterization was used.

In the analyses of the standardized coefficients (SC) for the construction of the latent variables (confirmatory factor analysis), a factor loading higher than 0.5 with p < 0.05 was considered to indicate acceptable correlation between the indicator variable and the construct 2525. Kline RB. Principles and practice of structural equation modeling. New York: The Guilford Press; 2016..

Direct and indirect effects of the latent and observed variables were assessed in the final model, with an effect being assumed to be present when p < 0.05.

The modindices command was used for suggestions of modifications of the initial hypothesis. When the value of the modification index was higher than 10 and the proposed modifications were theoretically plausible, a new model was elaborated and analyzed.

The final São Luís model was re-tested using the sample from Ribeirão Preto for validation.

Ethics statement

The project and consent form for participation in the BRISA study, including the investigation of violence against pregnant women, were approved by the Research Ethics Committees of the University Hospital of the Federal University of Maranhão (protocol n. 4771/2008-30) and the University Hospital of the Ribeirão Preto Medical School, University of São Paulo (protocol n. 4116/2008).

Results

In the city of São Luís, the ages of pregnant women ranged from 14 to 45 years (median 26 years) and intimate co-resident partners from 17 to 67 years (median of 29 years). In Ribeirão Preto, the ages of the pregnant women had a median of 25, ranging from 12 to 45 years, and their partners ranged from 15 to 63, with a median of 29 years.

The percentage of pregnant women belonging to families of economic class A/B was higher in Ribeirão Preto (26.7%) than in São Luís (15.5%). In more than 70% of families in both municipalities, the person with the highest income had a manual occupation. The percentage of pregnant women with 9 or more years of schooling was higher in São Luís (86.8%) than in Ribeirão Preto (71.4%). In both municipalities, approximately 70% of the intimate partners were older than the pregnant women (68.9% in São Luís and 71.7% in Ribeirão Preto) and about 50% of them had occupations with higher status than the women. Individuals with higher income were more frequently co-residing with intimate partners (approximately 60% in São Luís and 66% in Ribeirão Preto). About 11% of women interviewed were the highest earners in the family in the two municipalities. In Ribeirão Preto, the percentage of women who had white skin color (50.8%) was three times as high as in São Luís (16.6%). There were more catholic women in São Luís than in Ribeirão Preto (Table 2).

Table 2 Characteristics of pregnant women, their intimate partners and the person with the highest income in the family. São Luís (Maranhão State) and Ribeirão Preto (São Paulo State) prenatal cohorts, Brazil, 2010-2011.

The prevalence of overall intimate partner violence was 29.8% in São Luís, with 7.3% of women reporting one episode, 5.7% reporting few episodes, and 16.8% reports of many episodes. In Ribeirão Preto, the prevalence was 20.1%, with 3.9% of the subjects reporting one episode, 4% reporting a few episodes, and 12.2% many episodes. The occurrence of psychological violence and physical violence was greater in São Luís than in Ribeirão Preto, but there was no difference between these two municipalities in relation to sexual violence (Table 1).

The proposed model showed acceptable fit for the RMSEA, CFI and TLI indicators (Table 3) and there were no plausible suggestions for modification. Each indicator of the latent variables had factor loadings higher than 0.5 with p-values of less than 0.001, except for occupation of the person with the highest income in the family in both São Luís and Ribeirão Preto (Table 4).

In São Luís, pregnant women were more likely to suffer exclusive psychological violence by a co-residing intimate partner if they had the highest income in the family (SC = -0.202; p-value, p = 0.002). This was mainly a direct effect (SC = -0.182, p = 0.005), but there was also a smaller indirect effect mediated by low social support (SC = -0.020, p = 0.047). Also in São Luís, physical/sexual violence by a co-residing intimate partner was reported more frequently by women with higher educational attainment than their partners (SC = -0.466, p = 0.007), and among those who earned the highest income in the family (SC = -0.184, p = 0.035). Effects on physical/sexual violence related to the woman having the highest income in the family occurred only indirectly, mediated by low social support (SC = -0.040, p = 0.023) (Table 4).

The results for Ribeirão Preto showed that exclusive psychological violence was more frequent among pregnant women who earned the highest income in the family (SC = -0.189, p = 0.007) and when the co-residing intimate partners had higher status occupations than the women (SC = 0.236, p = 0.004). In addition to the direct effects of these two variables on exclusive psychological violence, there was a small indirect negative effect of a higher status occupation of the intimate partner (SC = -0.061, p = 0.030) mediated by the woman having the highest income in the family (SC = -0.05, p = 0.027). Also, in Ribeirão Preto, physical/sexual violence was more frequent when the income of the woman was higher than that of her co-residing intimate partner (SC = -0.217, p = 0.021). This was a direct effect (SC = -0.235, p = 0.010) without evidence of mediation (Table 4).

Discussion

In the municipalities of São Luís and Ribeirão Preto, pregnant women who had the highest income in the family were more frequently submitted to exclusive psychological and physical/sexual violence by an intimate partner. In São Luís, women with higher schooling than their partners also reported more episodes of physical/sexual violence. Thus, it seems that women who challenge traditional gender roles are at higher risk of suffering intimate partner violence, although in Ribeirão Preto psychological violence was more frequent when the women had lower status occupations than their partners.

Women’s empowerment due to a higher income may have resulted in challenges to the gender rules that historically justify male authority over female behavior, resulting in exclusive psychological and physical/sexual violence. From this perspective, as women gain more power through their income, they deviate from traditional gender roles and start to question and challenge the dominant masculine culture, causing men to feel threatened and to resort to violence as a way of asserting their traditional roles of command in the family 1111. Schraiber LB, d'Oliveira AFPL, Falcão NTC, Figueiredo WS. Violência dói e não é direito: a violência contra a mulher, a saúde e os direitos humanos. São Paulo: Universidade Estadual Paulista; 2005.,1313. Bjelland HF. En voldsom maktbalanse? En studie av relativ makt og forekomst av partnervold. Sosiologisk Tidsskrift 2014; 22:51-74.,2929. Antai D. Controlling behavior, power relations within intimate relationships and intimate partner physical and sexual violence against women in Nigeria. BMC Public Health 2011; 11:511.,3030. Jewkes R. Intimate partner violence: causes and prevention. Lancet 2002; 359:1423-29..

Low social support mediated the association between women having higher income and the physical-sexual violence in São Luís. Low social support was tested as a mediating risk factor for violence against women because an inadequate social network may facilitate female isolation and violence against them 3030. Jewkes R. Intimate partner violence: causes and prevention. Lancet 2002; 359:1423-29..

A study of 1,791 women and 1,640 men in Norway that investigated the association between partners’ power relations and the occurrence of intimate partner violence detected an almost seven-fold increased risk of psychological and physical violence by an intimate partner when the woman’s income was much higher than that of her partner. The explanation suggested by the authors was the fact that a man with an inferior status compared to his partner would feel less able to exert his masculinity and to fulfill socially expected traditional gender roles 1313. Bjelland HF. En voldsom maktbalanse? En studie av relativ makt og forekomst av partnervold. Sosiologisk Tidsskrift 2014; 22:51-74.. Another study, including 19,216 Nigerian women, also revealed that women who earned more than their spouses suffered more physical violence, a fact attributed by the authors to inequalities in relationships 2929. Antai D. Controlling behavior, power relations within intimate relationships and intimate partner physical and sexual violence against women in Nigeria. BMC Public Health 2011; 11:511..

In Brazilian society, the traditional expectation is that men, usually older, better educated and better paid than their female partners (or otherwise the only source of income for the couple), will more often hold socially valued positions and provide economically for the family; whereas their wives will take care of the home and children, executing unpaid work 1111. Schraiber LB, d'Oliveira AFPL, Falcão NTC, Figueiredo WS. Violência dói e não é direito: a violência contra a mulher, a saúde e os direitos humanos. São Paulo: Universidade Estadual Paulista; 2005.,3535. Saffioti H, Almeida SA. Violência de gênero: poder e impotência. Rio de Janeiro: Revinter; 1995.. Given this scenario, increased tensions may arise in relationships due to neglected housework, as women also gain higher education, wages and occupational status, and this may increase the controlling behavior of men and the risk of intimate partner violence for their partners 1111. Schraiber LB, d'Oliveira AFPL, Falcão NTC, Figueiredo WS. Violência dói e não é direito: a violência contra a mulher, a saúde e os direitos humanos. São Paulo: Universidade Estadual Paulista; 2005..

The prevalence of intimate partner violence in São Luís and Ribeirão Preto was higher than those found in other studies 33. World Health Organization. WHO multi-country study of women's health and domestic violence against women: summary report of initial results on prevalence, health outcomes and women's responses. Geneva: Word Health Organization; 2005.,1010. Brownridge DA, Tallieu TL, Tayler KA, Tiwari A, Chan KL. Pregnancy and intimate partner violence: risk factors, severity, and health effects. Violence Against Women 2011; 17:858-81.. It may be that the use of a self-applied instrument, without the interference of an interviewer, contributed to this finding. In addition, before completing the self-administered questionnaire, it was stated that women would not have their answers identified, as their names were not recorded in the data collection instruments. Finally, violence against pregnant women was not the central issue in the BRISA survey. Violence was presented as one of the probable “causes of prematurity”, as well as maternal hypertension, depression and racial discrimination, which may have encouraged women to report the episodes of violence suffered.

The strengths of the present study are: (a) the use of structural equation modeling in the analyses, which permitted us to study how dichotomous, ordinal and latent categorical variables determine violence by intimate partners, and reduce measurement error; (b) in a conceptual model, we were able to investigate differences in age, income, occupation and years of study between intimate partners, as indicators of gender inequalities in the relationship of the couple; and (c) we validated this conceptual model in samples from two different municipalities with contrasting realities using the same methodology, thus increasing the robustness of the findings.

The limitations of this study were that the sample was not selected to be representative of the population of pregnant women in the two municipalities, data from non-residing intimate partners were not included, and there were some missing data on economic class and family income. Another limitation is that the elaboration of a conceptual model does not contemplate all the factors that determine the occurrence of violence, thus always being merely an approximation of reality. Although the study was based on convenience sampling, it should be considered that the sample was not obtained from services that primarily provide care for pregnant women in situations of violence, but was obtained from prenatal care services for pregnant women with different levels of gestational risk and in different socioeconomic and demographic situations. As such the study was able to address key issues of diversity, across racial, economic, educational, religious and age dimensions. Indeed, analysis of diversity between women of different socioeconomic conditions, and how that relates to their experiences of intimate partner violence, was the key objective of the study. Although the prevalence of intimate partner violence was higher than that found in other studies, it is possible that there was some degree of measurement bias (underreporting of violence). However, care was taken to ensure a confidential private environment and the questionnaire was self-administered, which tends to reduce this type of bias.

The present findings suggest that intimate partner violence in the municipalities of São Luís and Ribeirão Preto is gender-based and can be explained by gender inequalities that result in inversion of traditional gender roles and conservative male attitudes, so that empowerment of the pregnant woman by a higher income than her partner’s seems to determine all kinds of violence even in contrasting socioeconomic realities. The current findings can help professionals in prenatal health settings understand the determinants of intimate partner violence, and future follow-up of the cohort will help identify how these factors influence future life experiences of these women.

Acknowledgments

The authors wish to thank the women who kindly agreed to participate in the BRISA investigation, as well as the interviewers, without whose help the data could not have been collected. FAPESP (São Paulo State Research Foundation), CNPq (Brazilian National Research Council) and FAPEMA (Maranhão State Research Foundation).

United Nations. Review and appraisal of the implementation of the Beijing declaration and platform for action and the outcomes of the twenty-third special session of the General Assembly. New York: United Nations; 2014.

Table 2 Characteristics of pregnant women, their intimate partners and the person with the highest income in the family. São Luís (Maranhão State) and Ribeirão Preto (São Paulo State) prenatal cohorts, Brazil, 2010-2011.

Variables

São Luís

Ribeirão Preto

p-value

n

%

n

%

Variables measured in the prenatal period

Economic class *

884

< 0.001

D/E

140

14.7

107

12.1

C

667

69.8

541

61.2

A/B

148

15.5

236

26.7

Family income (in minimum wages)

962

851

< 0.001

Less than one

56

5.8

28

3.3

1 to less than 3

541

56.3

413

48.5

3 to less than 5

227

23.6

257

30.2

5 or more

138

14.3

153

18.0

Occupation of the person with the highest income in the family

937

902

< 0.001

Unskilled manual laborer

278

29.7

309

34.3

Semi-specialized manual laborer

383

40.9

434

48.1

Specialized manual laborer

51

5.4

45

5.0

Office duties

149

15.9

78

8.6

High-level professional

47

5.0

27

3.0

Administrator/Manager/Director/Owner

29

3.1

9

1.0

Years of study of the pregnant woman

991

925

< 0.001

0-4

14

1.4

37

4.0

5-8

117

11.8

228

24.6

9-11

746

75.3

586

63.4

12 or more

114

11.5

74

8,0

Differences in age between the women and the co-residing intimate partners

810

790

0.077

Pregnant woman - partner > 5 years

50

6.2

38

4.8

Pregnant woman - partner = 1-5 years

145

17.9

114

11.4

Pregnant woman - partner = 0

57

7.0

72

9.1

Partner - pregnant woman =1-5 years

302

37.3

327

41.4

Partner - pregnant woman > 5 years

256

31.6

239

30.3

Differences in schooling between the women and the co-residing intimate partners

798

731

< 0.001

Woman’s schooling > intimate partner

175

21.9

193

26.4

Woman’s schooling = intimate partner

540

67.7

426

58.3

Woman’s schooling < intimate partner

83

10.4

112

15.3

Differences in occupation between the women and the co-residing intimate partners

802

771

0.720

Woman’s occupation > intimate partner

341

42.5

343

44.5

Woman’s occupation = intimate partner

49

6.1

43

5.6

Woman’s occupation < intimate partner

412

51.4

385

49.9

Person with the highest financial contribution in the family

990

936

0.018

Pregnant woman

117

11.8

100

10.7

Others

282

28.5

220

23.5

Intimate partner

591

59.7

616

65.8

Variables measured at the time of the children’s birth

Woman’s self-reported skin color

992

943

< 0.001

White

165

16.6

479

50.8

Others

827

83.4

464

49.2

Woman’s religion

836

761

0.020

Catholic

540

64.6

448

58.9

Evangelical

296

35.4

313

41.1

* Economic class was categorized as D/E, C and A/B, based on ownership of assets and educational level of the person with the highest income in the family, with categories A and B having greater purchasing power.